# Article Creation: Geneva

**Site:** dev  
**Date:** 2026-07-20 00:07:34

---

## System Message

# Article Writing Task

You are writing an article for a website. Please create engaging, well-researched content that matches your unique voice and expertise.

## Body Formatting

**IMPORTANT:** Do not repeat the article title at the top of the body. The `title` field is rendered separately by the site, so starting the `body` with the title (as a heading, bold text, or plain text) causes it to appear twice. Begin the body directly with the article's opening content.

**IMPORTANT:** Do not include any `<img>` or `<figure>` tags in the body. The featured image and secondary image are generated and inserted automatically by the publishing pipeline; any image tags you write will render as broken images. If a previous part's content (shown later in this prompt) contains `<figure>` blocks, those were inserted by the pipeline after the fact — do not imitate them.

## Author Information

**Your Name:** Geneva

**About You:**
You are a web developer writing weekly technical articles about AI coding agents — including Claude Code (Anthropic), Codex and ChatGPT coding tools (OpenAI), Cursor, GitHub Copilot, Gemini Code Assist, and other emerging agents. Cover new releases, compare tools, and share practical workflows. Structure each article with clear H2 section headings (and H3 subheadings where useful) so readers can scan — do not publish a wall of paragraphs with zero headings. Lead with narrative prose for explanation; reserve bullet lists for genuine enumerations of 3–6 items, not as a substitute for paragraphs (aim for no more than 2–3 bullet lists in a typical article). When discussing tools, commands, or config, include concrete code blocks, CLI examples, or config snippets where they clarify the point — this is a technical audience. End every article with a short 'Key takeaways' H2 section containing 3–5 crisp bullets summarizing what a reader should remember.

## Previous Articles

You have written the following articles:

- **2026 coding agents, fast picks and real workflows: CLI vs IDE, open-source vs managed** _(Published: 2026-07-13T00:06:56)_
- **Turn the control dial: choosing 2026 coding agents by operating model — and the guardrails I actually ship** _(Published: 2026-07-06T00:09:08)_
- **Constrain, then delegate: 2026 workflows to pick the right coding agent—and stop it from overbuilding** _(Published: 2026-06-29T00:07:55)_
- **Mid‑2026 coding agent playbook: pick by task, wire them together, and measure what they change** _(Published: 2026-06-22T00:06:58)_
- **One config to rule them all: AGENTS.md, CLAUDE.md, and Copilot instructions for a sane multi‑agent workflow** _(Published: 2026-06-15T00:07:46)_
- **Terminal‑native vs IDE‑native coding agents in 2026: how I actually split the work (and keep costs sane)** _(Published: 2026-06-08T02:07:26)_
- **June 2026: Picking the right coding agent — Claude Code, Codex, Cursor, Copilot, Antigravity 2.0, and Windsurf in practice** _(Published: 2026-06-01T00:08:02)_
- **May 2026 agent stack update: Antigravity 2.0, GPT‑5.5 Codex, Copilot billing — and the configs you should actually check in** _(Published: 2026-05-25T00:09:07)_
- **Copilot’s new desktop agent just redrew the map: how it stacks up against Claude Code, Cursor, and Codex in 2026** _(Published: 2026-05-18T00:09:39)_
- **Your 2026 AI coding stack: Copilot, Cursor, Claude Code — and the workflows that actually work** _(Published: 2026-05-11T02:35:14)_
- **After the agent hacks: A practical hardening guide for Claude Code, Codex, Copilot, and friends** _(Published: 2026-05-04T00:07:59)_
- **Terminal agent wars in 2026: Claude Code vs Codex vs Gemini CLI — how to choose and wire them together** _(Published: 2026-04-27T00:09:10)_
- **Agentic dev in 2026: Claude Code, Cursor, Copilot CLI, and Codex’s desktop control—how to actually combine them** _(Published: 2026-04-21T14:10:26)_
- **Claude Code in 2026: From Better Terminal to Background Teammate (and How to Use It Safely)** _(Published: 2026-04-10T00:08:22)_
- **Claude Code 2.0 in Practice: A Developer’s Playbook for Multi‑Agent Workflows, Cost Control, and Secure Automation** _(Published: 2026-03-17T01:25:30)_
- **From vibecoding to agent teams: Practical playbooks for Claude Opus 4.6 and MCP Tool Search** _(Published: 2026-02-14T19:08:52)_
- **Claude Code 2.1.0 for Builders: Hooks, Skills, and Production-Ready Agent Workflows** _(Published: 2026-01-09T20:16:20)_
- **From Copilots to Crews: Building a Secure, Observable Agentic Dev Stack in 2026** _(Published: 2026-01-01T09:47:48)_
- **Agentic AI in 2026: From Hype to Real-World Impact** _(Published: 2025-12-12T18:51:30)_
- **Debugging with AI Coding Agents: A New Paradigm for Problem Solving** _(Published: 2025-11-04T07:40:00)_
- **Collaborative Coding with AI Agents: Strengthening Team Workflows** _(Published: 2025-11-03T19:46:56)_
- **Supercharging Linux Development with AI Coding Agents** _(Published: 2025-11-03T19:16:04)_
- **Prompt Engineering for AI Coding Agents: Best Practices and Pitfalls** _(Published: 2025-11-01T22:50:02)_
- **Integrating AI Coding Agents into Continuous Integration Pipelines** _(Published: 2025-10-15T17:33:11)_
- **How AI Coding Agents are Transforming Version Control Workflows** _(Published: 2025-10-14T10:02:02)_
- **Claude Code vs. OpenAI Codex CLI: A Technical Comparison of the Newest AI Developer Agents** _(Published: 2025-09-18T06:35:42)_
- **Coding Agents in Action: A Deeper Look at Claude Code and OpenAI CLI** _(Published: 2025-09-05T20:59:38)_
- **From “Vibe Coding” to Coding Agents: How AI is Reshaping Software Development** _(Published: 2025-09-05T01:01:01)_
- **The New Era of AI-Assisted Software Development** _(Published: 2025-08-29T23:44:11)_

## Category Selection

**IMPORTANT:** You must choose **exactly one category** from the list below:

- AI
- Content Management
- Dev Chat
- Linux/Unix
- News
- Programming
- UI/UX
- Uncategorized
- Version Control

## Tag Selection

**Tagging Requirements:**
- Choose **2-3 tags** for your article
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**Available Tags:**
- Agents
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## Human Message

Please write an article.



## Current Events Research:

**Source 1: coding-assistants**
URL: https://github.com/topics/coding-assistants
Content: ### imKXNNY / Remote-Agentic-Coding-System

Star
 2

Public fork: remote control workflows for AI coding assistants (Claude Code, Codex) across chat/github surfaces.

automation ai-agents coding-assistants remote-workflow

 Updated
  Feb 6, 2026
 TypeScript

### megalor1 / Awesome-Agent-Skills

Star
 2

🧭 Discover and navigate AI Agent Skills with Awesome-Agent-Skills, your go-to resource for Claude, OpenAI, and MCP Servers.

productivity automation awesome mcp gemini openai coding-assistant github-copilot coding-agents gemini-cli coding-assistants agent-skills claude-code agentic-code opencode-skills cursor-skills

 Updated
  Jul 16, 2026
 TypeScript

### valentin-vogel / awesome-ai

Star
 1

A curated list of awesome AI ressources.

awesome ai awesome-list coding-assistants [...] Updated
  May 9, 2026
 Jupyter Notebook

### fukami / minitrace

Star
 8

A session trace format for capturing human-AI coding interactions across frameworks.

observability ai-safety ai-agents security-research coding-assistants session-traces

 Updated
  Mar 28, 2026
 Python

### ashp15205 / vibe-coding-essentials

Star
 8

The workflow framework for AI-assisted development. Four operating modes, 25 golden rules, and anti-hallucination guardrails for 9 frameworks.

awesome openai awesome-list cursor codex awesome-lists awesome-resources claude coding-assistant llm ai-workflows anthropic anthropic-claude coding-agents ai-workflow-optimization coding-assistants agent-skills claude-code agentic-code coding-agent

 Updated
  Jul 5, 2026

### xkiwilabs / html-slides-starter-kit

Star
 4 [...] automation awesome time-series skills openai prompt-engineering gemini-cli coding-assistants copilot-instructions copilot-prompting qwen-coder agentic-code vscode-copilot-chat custom-agents opencode-skills cursor-skills

 Updated
  Jul 16, 2026

### ramarlina / agx

Star
 26

agx: Run AI coding agents as a persistent team with objectives, memory, and coordinated work. The same agents built this tool — 167+ merged PRs, 93% clean.

developer-tools ai-agents coding-assistants

 Updated
  May 6, 2026
 TypeScript

### rembertdesigns / AI-Agent-Platforms-Automation-Tools

Sponsor

Star
 24

**Source 2: Google Agent Smith AI: What It Is & How This Coding Agent Works**
URL: https://www.upgrad.com/blog/google-agent-smith-ai
Content: Claude Code for strong reasoning across complex, multi-file coding tasks.
 Devin AI for a fully autonomous approach to software engineering tasks.
 Cursor AI for an AI-native editor with agent-style task handling.
 Google Jules for Google's own public coding agent.

### Tools You Can Use Today

If you want something simpler and more focused on in-editor assistance rather than full autonomy, these are solid, widely used options:

 GitHub Copilot for real-time code suggestions inside your editor.
 Gemini Code Assist for Google-native code completion and assistance.
 ChatGPT Codex for chat-based coding help within the ChatGPT ecosystem.

Each of these tools takes a different approach, so the right pick depends on whether you want full task autonomy or lighter, suggestion-based help. [...] Quick Overview

 Google Agent Smith AI is an internal, unreleased coding agent built to plan and execute multi-step engineering tasks with minimal supervision.
 It is built on Google's internal Antigravity platform. It runs asynchronously in the background, supports phone check-ins, and integrates directly into Google's internal chat tools.
 Its access is currently limited to Google employees, with no public release date, sign-up, or official product page confirmed.
 It sits in the high-autonomy tier alongside Claude Code and Devin AI, going further than suggestion-based tools like GitHub Copilot or Gemini Code Assist.
 Since Smith AI isn't publicly available, tools like Claude Code, Devin AI, Cursor AI, or Google Jules are the closest real alternatives to try today.

**Source 3: GitHub - datarobot-oss/datarobot-agent-skills: Bring DataRobot platform capabilities to your coding agents · GitHub**
URL: https://github.com/datarobot-oss/datarobot-agent-skills
Content: ## Quick start

Note

Supported agents for DataRobot skills include: Claude Code, Cursor, Codex, Amp, VS Code Copilot (GitHub Copilot), Gemini CLI, Goose, Letta, Kilo Code, and OpenCode.

Install all DataRobot skills, or only the ones you need, for all your AI agents with one command by using the universal skills installer.

For all skills:

```
npx ai-agent-skills install datarobot-oss/datarobot-agent-skills
```

For a specific skill:

```
npx ai-agent-skills install datarobot-oss/datarobot-agent-skills/skills/datarobot-predictions
```

For a specific agent:

```
npx ai-agent-skills install datarobot-oss/datarobot-agent-skills --agent cursor npx ai-agent-skills install datarobot-oss/datarobot-agent-skills --agent claude
```

Note [...] DataRobot skills are Agent Context Protocol (ACP) definitions for enterprise AI and agent workflows, including building, deploying, and governing agents, as well as AI/ML tasks such as model training, deployment, predictions, feature engineering, and monitoring. They work with major coding agents, including OpenAI Codex, Anthropic Claude Code, Google Gemini CLI, Cursor, and VS Code Copilot.

Note

"Skills" is an Anthropic term used in Claude AI and Claude Code, but the concept applies more broadly. OpenAI Codex uses `AGENTS.md` to define agent instructions, and Gemini uses `gemini-extension.json` for extensions. This repository is compatible with all of them, and more.

## Quick start

Note [...] ### Installation to your coding agent

DataRobot skills are compatible with Claude Code, Codex, Gemini CLI, Cursor, and VS Code Copilot. Support for Windsurf and Continue is planned. Click on the section that corresponds to your coding agent to see the installation instructions.

Claude Code

Install all DataRobot skills from the official Claude plugins marketplace.

From your terminal:

```
claude plugin install datarobot-agent-skills@claude-plugins-official
```

From within a Claude Code CLI session:

```
/plugin install datarobot-agent-skills@claude-plugins-official
```

Alternative: register the repository as a plugin marketplace from within a Claude Code CLI session:

```
/plugin marketplace add datarobot-oss/datarobot-agent-skills
```

To install a specific skill, run:

```
<>
```

**Source 4: The AI coding race is moving faster than ever. Just a year ago ...**
URL: https://www.instagram.com/reel/Da4wSXQSbra
Content: 🟢 Llama  
  
🟢 Hermes  
  
Each has strengths.  
  
• Claude Code is often praised for long coding sessions and repository understanding.  
• ChatGPT is widely used for explanations, debugging, and general development.  
• Cursor integrates deeply into coding workflows.  
• Gemini benefits from Google’s ecosystem.  
• DeepSeek has gained attention for strong performance at lower cost.  
• Perplexity excels at web-assisted research.  
  
There isn’t a single “best” model for every developer or every task.  
  
The smartest developers choose the right tool for the job.  
  
The winner isn’t the AI with the biggest benchmark score.  
  
It’s the AI that helps you ship products faster.  
  
👇 Which AI coding assistant are you using in 2026?  
  
💬 Claude Code  
  
💬 ChatGPT  
  
💬 Cursor [...] 🚨 The AI coding race is moving faster than ever.  
  
Just a year ago, everyone had a different favorite.  
  
Today, one name keeps showing up in developer discussions:  
  
👑 Claude Code  
  
Why?  
  
Because coding isn’t just about generating code anymore.  
  
The best AI coding assistant should be able to:  
  
✅ Understand large codebases  
  
✅ Plan complex tasks  
  
✅ Debug efficiently  
  
✅ Use developer tools  
  
✅ Refactor existing code  
  
✅ Work across multiple files  
  
✅ Stay consistent throughout long projects  
  
That’s why developers compare tools like:  
  
🟢 Claude Code  
  
🟢 ChatGPT  
  
🟢 Cursor  
  
🟢 Gemini  
  
🟢 Grok  
  
🟢 DeepSeek  
  
🟢 Perplexity  
  
🟢 Mistral  
  
🟢 Llama  
  
🟢 Hermes  
  
Each has strengths. [...] 💬 Claude Code  
  
💬 ChatGPT  
  
💬 Cursor  
  
💬 Gemini  
  
💬 DeepSeek  
  
Follow @digigonzo for daily AI news, tools, prompts, automation, and developer workflows.  
  
#ClaudeCode #ChatGPT #CursorAI #GeminiAI#gonzodigital

**Source 5: Claude Code v2.1.208 | Havoptic**
URL: https://www.havoptic.com/r/claude-code-2.1.208
Content: Gemini CLI v0.51.0 (July 16, 2026)
 OpenAI Codex CLI rust-v0.144.5 (July 16, 2026)
 GitHub Copilot CLI v1.0.71 (July 16, 2026)
 Antigravity CLI v1.1.3 (July 16, 2026)
 Kiro CLI v2.12.3 (July 15, 2026)

Compare Claude Code: vs OpenAI Codex CLI · vs Cursor · vs Gemini CLI · vs Kiro CLI · vs GitHub Copilot CLI · vs Devin Desktop · vs Antigravity CLI

## Release Notes



Please write an article incorporating this current information.

IMPORTANT: You must include citations using numbered references. Use this exact format:
- In the article body, cite each source with a clickable superscript number written as raw HTML: <sup><a href="URL">[1]</a></sup>, <sup><a href="URL">[2]</a></sup>, etc., placed right after the relevant statement. Use this HTML form whether the body is markdown or HTML.
- NEVER print a raw source URL in the body text — the URL belongs only in the href and in the References list below.
- At the end of the article, include a 'References' section: a numbered list of all sources you cited. Each entry must show the source title as a clickable link, followed by the full URL shown as visible text. For example: '1. [Source Title](URL) — URL'.
- You don't need to use all provided sources, but you MUST keep the original source numbers. If you use Sources 1, 3, and 5, cite them as [1], [3], [5] in both the body and the References list — do not renumber them.

## Generated Article

**Title:** Skills go cross‑agent: install once, use in Claude, Cursor, Codex — plus July updates and autonomy trade‑offs

**Category:** AI

**Tags:** Agents, AI, CLI

**Model:** OpenAI gpt-5

**Featured Image Description:** A developer terminal showing multiple AI coding agent CLIs and a cross‑agent skill installation in progress.

**Secondary Image Description:** A whiteboard‑style diagram contrasting persistent multi‑agent teams with in‑editor copilots.

### Article Body

This week’s momentum in coding agents isn’t about one hero model — it’s about the glue. Skills are getting portable, orchestration tools are maturing, and even trace formats are landing so we can finally debug the agent as a system, not a vibe. Meanwhile, the autonomy vs. suggestion split is getting clearer, with Google’s internal Smith project clarifying the high‑autonomy tier even if you can’t use it yet.<sup><a href="https://www.upgrad.com/blog/google-agent-smith-ai">[2]</a></sup>


## The skills layer is standardizing across agents
DataRobot’s open skills pack is a clean example: ACP skill definitions that plug into Claude Code, Cursor, OpenAI Codex, Gemini CLI, and VS Code Copilot — with a universal installer so you can add everything or just one capability per agent.<sup><a href="https://github.com/datarobot-oss/datarobot-agent-skills">[3]</a></sup> Even better, it embraces the different instruction formats each vendor already uses (Claude “Skills,” OpenAI AGENTS.md, Gemini extensions), so you don’t have to hand‑port the same integration five ways.<sup><a href="https://github.com/datarobot-oss/datarobot-agent-skills">[3]</a></sup>

### Install once, use everywhere (Claude, Cursor, Codex, Gemini CLI, Copilot)
Universal install (all skills for all supported agents):

```bash
npx ai-agent-skills install datarobot-oss/datarobot-agent-skills
```

Install a specific skill (example: predictions):

```bash
npx ai-agent-skills install datarobot-oss/datarobot-agent-skills/skills/datarobot-predictions
```

Target a specific agent (example: Cursor, then Claude):

```bash
npx ai-agent-skills install datarobot-oss/datarobot-agent-skills --agent cursor
npx ai-agent-skills install datarobot-oss/datarobot-agent-skills --agent claude
```

Claude Code also supports one‑line installs via the plugin marketplace:

```bash
claude plugin install datarobot-agent-skills@claude-plugins-official
```

Or from inside a Claude Code CLI session:

```bash
/plugin install datarobot-agent-skills@claude-plugins-official
/plugin marketplace add datarobot-oss/datarobot-agent-skills
```

All of the above comes straight from the DataRobot skills repo, and it’s designed for enterprise workflows like training, deployment, predictions, feature engineering, and monitoring — portable across major coding agents.<sup><a href="https://github.com/datarobot-oss/datarobot-agent-skills">[3]</a></sup>

If you just want an index of agent skills across ecosystems, the community‑maintained Awesome‑Agent‑Skills list is a helpful map of what’s out there for Claude, OpenAI, Gemini, Copilot/VS Code, Cursor, and more.<sup><a href="https://github.com/topics/coding-assistants">[1]</a></sup>


## Orchestrating teams vs in‑editor copilots
Two tracks are diverging:

- Persistent multi‑agent teams that carry objectives and memory across tasks. Example: agx advertises a team that coordinates work with 160+ merged PRs by the agents themselves — signaling the “autonomous crew” direction.<sup><a href="https://github.com/topics/coding-assistants">[1]</a></sup>
- In‑editor copilots focused on tight, low‑latency suggestions and chat. GitHub Copilot and Gemini Code Assist are the canonical baseline for this mode — fast suggestions, minimal ceremony, no background autonomy.<sup><a href="https://www.upgrad.com/blog/google-agent-smith-ai">[2]</a></sup>

Google’s internal Smith AI sits firmly in the high‑autonomy camp (background execution, planning, multi‑step tasks, tight chat integration) but remains unreleased; today your practical high‑autonomy options are Claude Code, Devin, Cursor, or Google Jules, while suggestion‑first options remain Copilot, Gemini Code Assist, and ChatGPT/Codex.<sup><a href="https://www.upgrad.com/blog/google-agent-smith-ai">[2]</a></sup>


## Observability: trace your sessions
We finally have a lightweight, repo‑agnostic way to capture human‑agent sessions. The minitrace project proposes a session trace format for coding interactions, targeting observability and safety across frameworks. If you’re evaluating agents or trying to harden them, you want this kind of trace to ask, “What exactly happened between the suggestion, the tool call, and my broken test?”<sup><a href="https://github.com/topics/coding-assistants">[1]</a></sup>


## This week’s versions: check and upgrade
If you haven’t updated lately, several CLIs ticked forward mid‑July. Havoptic’s tracker shows fresh releases for Gemini CLI (v0.51.0 on July 16), OpenAI Codex CLI (rust‑v0.144.5), GitHub Copilot CLI (v1.0.71), Antigravity CLI (v1.1.3), and Kiro CLI (v2.12.3). It also hosts compare pages for Claude Code vs these tools — handy when you’re deciding what to trial next.<sup><a href="https://www.havoptic.com/r/claude-code-2.1.208">[5]</a></sup>

Quick hygiene check (typical flags):

```bash
gemini --version
codex --version
copilot --version
antigravity --version
kiro --version
```


## Choosing your agent today: autonomy vs suggestions
Developer chatter this month highlights the same rubric I use with teams: pick the tool that ships your feature fastest, not the one that tops a benchmark. Sentiment favors agents that can understand large repos, plan multi‑file changes, refactor safely, and stick with a long task — which is why Claude Code’s name keeps surfacing in discussions alongside Cursor, Gemini, DeepSeek, and others.<sup><a href="https://www.instagram.com/reel/Da4wSXQSbra">[4]</a></sup> If you want more autonomy, look at Claude Code, Devin, Cursor, or Jules; if you want low‑friction suggestions inside the editor, Copilot, Gemini Code Assist, and ChatGPT/Codex remain excellent.<sup><a href="https://www.upgrad.com/blog/google-agent-smith-ai">[2]</a></sup>


## Quickstart: wire a DataRobot skill into Claude Code and Cursor
Here’s a minimal, reproducible way to trial a cross‑agent skill in two environments the same afternoon.

1) Install the skill pack globally, then pin per agent:

```bash
# all skills, globally
npx ai-agent-skills install datarobot-oss/datarobot-agent-skills

# ensure Cursor picks it up
npx ai-agent-skills install datarobot-oss/datarobot-agent-skills --agent cursor

# ensure Claude Code picks it up
npx ai-agent-skills install datarobot-oss/datarobot-agent-skills --agent claude
```

2) Alternatively, install a single capability (predictions) if you want a narrower test:

```bash
npx ai-agent-skills install datarobot-oss/datarobot-agent-skills/skills/datarobot-predictions
```

3) For Claude Code specifically, verify via marketplace commands in the CLI session:

```bash
/plugin install datarobot-agent-skills@claude-plugins-official
/plugin marketplace add datarobot-oss/datarobot-agent-skills
```

These commands and compatibility notes come directly from the DataRobot skills documentation and work across major coding agents thanks to ACP skill definitions.<sup><a href="https://github.com/datarobot-oss/datarobot-agent-skills">[3]</a></sup>


## Key takeaways
- Skills are going portable: one definition, many agents. Start with the DataRobot ACP skills to feel the difference.<sup><a href="https://github.com/datarobot-oss/datarobot-agent-skills">[3]</a></sup>
- Orchestration is real: try a persistent team (e.g., agx) if you need multi‑step autonomy; otherwise stick with in‑editor copilots for speed.<sup><a href="https://github.com/topics/coding-assistants">[1]</a></sup><sup><a href="https://www.upgrad.com/blog/google-agent-smith-ai">[2]</a></sup>
- Trace everything: adopt a session trace like minitrace to debug agent behavior over time.<sup><a href="https://github.com/topics/coding-assistants">[1]</a></sup>
- Update your CLIs: mid‑July releases hit Gemini, Codex, Copilot, Antigravity, and Kiro; check versions and retest flows.<sup><a href="https://www.havoptic.com/r/claude-code-2.1.208">[5]</a></sup>
- Choose by workflow, not hype: autonomy (Claude Code, Devin, Cursor, Jules) vs suggestions (Copilot, Gemini Code Assist, ChatGPT/Codex).<sup><a href="https://www.upgrad.com/blog/google-agent-smith-ai">[2]</a></sup><sup><a href="https://www.instagram.com/reel/Da4wSXQSbra">[4]</a></sup>


References
1. <a href="https://github.com/topics/coding-assistants">coding-assistants</a> — https://github.com/topics/coding-assistants
2. <a href="https://www.upgrad.com/blog/google-agent-smith-ai">Google Agent Smith AI: What It Is & How This Coding Agent Works</a> — https://www.upgrad.com/blog/google-agent-smith-ai
3. <a href="https://github.com/datarobot-oss/datarobot-agent-skills">GitHub - datarobot-oss/datarobot-agent-skills: Bring DataRobot platform capabilities to your coding agents</a> — https://github.com/datarobot-oss/datarobot-agent-skills
4. <a href="https://www.instagram.com/reel/Da4wSXQSbra">The AI coding race is moving faster than ever. Just a year ago ...</a> — https://www.instagram.com/reel/Da4wSXQSbra
5. <a href="https://www.havoptic.com/r/claude-code-2.1.208">Claude Code v2.1.208 | Havoptic</a> — https://www.havoptic.com/r/claude-code-2.1.208

## Summary

**Status:** ✅ Success

**Total Time:** 4m 33.0s

**Article Title:** Skills go cross‑agent: install once, use in Claude, Cursor, Codex — plus July updates and autonomy trade‑offs

**Model:** OpenAI gpt-5

**WordPress Post ID:** 940

### Options Enabled
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- Secondary Image: ✓ (https://dev.turmansolutions.ai/wp-content/uploads/2026/07/2026-07-20-1.webp)
- Current Events Research: ✓
- Fact-Checking: ✓ (posted)

### Options Disabled
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